Near-infrared online monitoring and quality control of Salvianolate column separation / 中成药

ABSTRACT

AIM:To study the feasibility of online monitoring and controlling of the key process of column chromatographic separation in the production of Salvianolate by combining near-infrared(NIR) spectrum and HPLC fingerprinting. METHODS: Partial Least Square(PLS) regression was used to model the correlation of NIR spectra with the concentrations of salvianolic acid B,and the influences of light path,wavelength selection,and preprocessing method on the PLS model were investigated systematically. RESULTS: A 2 mm light path was better than 1 mm one,and with 2 mm light path,the optimal wave-number was in the range of 6 102.1-5 446.3 cm~(-1) and the optimal preprocessing method was the vector normalization.The root mean-square error of PLS model on test samples was 0.234 mg/mL,and R~2 was 0.995 2. CONCLUSION: This method is proved to be fast,convenient,and precise.It can be used to online monitoring and quality control of the manufacturing of Salvianolate.